In this course you will learn about how and why DNA and protein sequences evolve. You will learn the theory behind methods for building and analyzing phylogenetic trees, and get hands-on experience with some widely used software packages.
This course is about molecular evolution - the evolution of DNA, RNA, and protein molecules. The focus is on computational methods for inferring phylogenetic trees from sequence data, and the course will cover the fundamental theory and algorithms, while also giving the student hands-on experience with some widely used software tools. Since evolutionary theory is the conceptual foundation of biology (in the words of Theodosius Dobzhansky: "Nothing in biology makes sense except in the light of evolution"), what you learn on this course will be relevant for any project you will ever do inside the life sciences. A phylogenetic tree will almost always help you think more clearly about your biological problem.
In this course you will learn a whole lot of modern physics (classical and quantum) from basic computer programs that you will download, generalize, or write from scratch, discuss, and then hand in. Join in if you are curious (but not necessarily knowledgeable) about algorithms, and about the deep insights into science that you can obtain by the algorithmic approach.
This course provides a broad introduction to the field of nonlinear dynamics, focusing both on the mathematics and the computational tools that are so important in the study of chaotic systems. The course is aimed at students who have had at least one semester of college-level calculus and physics, and who can program in at least one high-level language (C, Java, Matlab, R, ...).